Sensors are everywhere, facilitating real-time decision making and actuation, and informing policy choices. But extracting information from sensor data is far from straightforward: sensors are noisy, prone to decalibrate, and may be misplaced, moved, compromised, and generally degraded over time. We understand very little about the issues of programming in the face of pervasive uncertainty, yet sensor-driven systems essentially present the designer with uncertainty that cannot be engineered away. Moreover uncertainty is a multi-level phenomenon in which errors in deployment can propagate through to incorrectly-positioned readings and then to poor decisions; system layering breaks down when exposed to uncertainty. How can we be assured a sensor system does what we intend, in a range of dynamic environments, and how can we make a system ``smarter'' ? Currently we cannot answer these questions because we are missing a science of sensor system software. We will develop the missing science that will allow us to engineer for the uncertainty inherent in real-world systems. We will deliver new principles and techniques for the development and deployment of verifiable, reliable, autonomous sensor systems that operate in uncertain, multiple and multi-scale environments. The science will be driven and validated by end-user and experimental applications.

Thales are the leading company in Europe for high performance long wavelength infra-red (LWIR) imagers. Thales has been developing thermal imagers for more than 40 years, and is currently working on a unique polarimetric thermal imaging camera concept - the Polarimetric Catherine MP. Thermal imagers provide day and night imaging capability with good object discrimination (for example, telling the difference between animals and vehicles). Further development work has been identified to progress the current camera capabilities. This work includes advanced signal, data and image processing development, some of which are already underway in house. The proposed project is integral part of this effort as it will address fundamental issues about the operation and performance of the detector, as well as investigating a novel approach to utilising the camera data (thermal and polarisation imagery) for deployment as part of a multi-modal imaging system. This will be achieved primarily through the application of existing expertise in Bayesian inference, imaging and polarisation in STFC-funded research groups (Astronmy and Institute of Gravitational Research) at the University of Glasgow. Algorithms will be developed with an aim to diagnosing and improving flat-fielding and polarimetric contrast. These algorithms will be tested using simulated data and test data acquired through experimentation and test field imaging. This project will coordinate and support in-house R&D of Thales polarimetric imagers and help the company gain a better understanding at all levels of this technology and maximise its application in different markets

Diamond and fibre are a natural match that provides a platform to take high-power lasers into hitherto unattainable parameter regimes and to serve new applications. Though attractive in its simplicity, this area remains largely unexplored. Here, we propose a partnership that will enable high-impact applications through careful investigation of the underpinning device science. This will lead to fibre-pumped diamond Raman lasers with properties tailored to applications in LIDAR and clear plastics processing. We aim to lay the foundations for this to become the preferred approach for a number of important laser applications. Fibre lasers are the laser of choice from medicine to materials processing thanks to their reliability, low cost of ownership, proven performance, and outstanding power scalability. While moderate laser parameters and standard wavelengths suffice for many applications, many more require better beam quality, narrower linewidths, specific wavelengths, or well-controlled high-energy pulses - but still at hundreds of watts of output power. Fibre lasers can only rarely simultaneously satisfy these requirements. In this project, we aim to overcome these generic limitations of fibre sources by employing diamond to shift fibre lasers further into infrared via stimulated Raman scattering (SRS) with simultaneous brightness enhancement and, in the case of pulses, spectral narrowing towards the transform-limit. The UK is established as a world leader in fibre laser research and has played a leading role in pioneering the use of diamond in Raman lasers. Both fibre lasers and diamond are recognized as being superbly power scalable thanks to superior optical and thermal properties. Our approach will harness the advantages of fibre systems - efficiency, compactness, and reliability - while modifying their output to better address key industrial challenges. While the combination of fibre and diamond is a platform solution that can address a wide range of wavelength-specific applications, especially in the near IR range, in this project we aim to prove the technology in two areas that are important for our industrial partners. This proposal will deliver a new type of laser that is uniquely capable of the combination of power, brightness, spectral purity and wavelength required for industrially important applications in LIDAR and clear plastic processing.

In a consortium led by Heriot-Watt with St Andrews, Glasgow, Strathclyde and Dundee, this proposal is for an EPSRC CDT in Applied Photonics and responds to the Integrative Technologies priority area, but also impacts on the Measurement and Sensing, Photonic Materials and Innovative Production Processes priorities. Technologies integrating photonics and electronics pervade products and services in any modern economy, enabling vital activities in manufacturing, security, telecommunications, healthcare, retail, entertainment and transport. The success of UK companies in this technology space is threatened by a lack of doctoral-level researchers with a grasp of photonic- / electronic-engineering design, fabrication and systems integration, coupled with high-level business, management and communication skills. By ensuring a supply of these individuals, our CDT will deliver broad-ranging impacts on the UK industrial knowledge base, driving the high-growth export-led sectors of the UK economy whose photonics-enabled products and services have far-reaching impacts on society, from consumer technology and mobile computing devices to healthcare and security. Building on the success of our current IDC in Optics and Photonics Technologies, the proposed CDT will again be configured as an IDC but will enhance our existing programme to meet industry's need for engineers able to integrate photonic and electronic devices, circuits and systems to deliver high value products and processes. Our proposal was developed in partnership with industry, whose letters of support show a commitment to sponsoring 71-74 EngD and 14-17 PhD projects -- 40% more than the minimum required -- demonstrating exceptional industrial engagement. Major stakeholders include Fraunhofer UK, NPL, Renishaw, Thales, BAE Systems, Gooch and Housego and Selex ES, who are joined by a number of SMEs. The CDT follows a model in which (annually) EPSRC funds 7 EngD students, with 3 more supported by industrial / university contributions. In a progressive strategy supported by our industrial partners, we will, where appropriate, align university-funded PhD projects to the programme to leverage greater industry engagement with PhD research in the consortium. The focus of the CDT corresponds to areas of research excellence in the consortium, which comprises 89 academic supervisors, whose papers since 2008 total 584 in all optics journals , with 111 in Science / Nature / PRL, and whose active EPSRC PI photonics funding is £40.9M. All academics are experienced supervisors, having each supervised on average >6 doctoral students, with many previously acting as IDC supervisors. The strategic commitment by the participating universities is evidenced by their recruitment since 2008 of 29 new academic staff in relevant areas (including 9 professors). An 8-month frontloaded residential phase in St Andrews and Glasgow will ensure the cohort strongly gels together, and will equip students with the technical knowledge and skills they need before they begin their industrial research project. Business modules (x3) will bring each cohort back to Heriot-Watt for 1-week periods, and weekend skills workshops will be used to regularly reunite the cohort, further consolidating it to create opportunities for peer-to-peer interactions. Taught courses will total 120 credits, and will be supplemented by new Computational Methods, Systems Integration and Research Skills workshops delivered by our industry partners, as well as public-engagement training led by Glasgow Science Centre. Another innovation is an International Advisory Board, comprising leading academics / industrialists , who will benchmark and advise on our performance. The requested EPSRC support of £4.5M is complemented by £2.8M of industrial / academic cash, covering the cost of 3 students in each cohort of 10. In-kind industrial / academic contributions are worth a further £5.4M, providing exceptional value.

Image processing is playing an increasingly important role in our lives whether this is the numerous sources of social provision e.g. TV, or the increased reliance on security to protect our everyday lives through the proliferation of security cameras in airports and town centres. There are also healthcare applications with increased need for 3-dimensional (3D) images such as in viewing 3D computerised tomography scans to provide much more intelligent treatment. In automotive applications, cameras are used for quality assurance in manufacture and situational awareness in use. In security applications, organisations are keen to have more intelligent views of scenes to highlight security risks and dangers. This has increased the amount of visual information that we process and store, and has placed increasing importance on the users' ability to process data where it is received, thus pushing for more intelligent image processing. Whilst a lot of innovative work has been done to derive the algorithms to provide this intelligence, there is a clear need for suitable, high performance, lower power hardware to provide the processing as in many cases, these systems may be remote e.g. security cameras with limited interconnection. We could wait for technology evolutions to provide the increased performance as before, but the warnings on process variability below 45-nm CMOS technology suggest that this might not be forthcoming and implies an increased focus on novel processor architectures is required. Whilst multi-core and application specific processors such as graphical processing units (GPUs) have been proposed, the gains have been limited. In addition, the rapid developments in the acquisition and interpretation of images together with intelligent algorithmic development, have not been matched by sound software engineering principles to develop and transform code into hardware implementations efficient in speed, memory and power. In many cases, image sensors comprise simple processing engines which communicate to some central resource for further processing. For a lot of medical and security applications, there is a need for more intelligent image acquisition, multi-view video processing (merging many views into a more useful, higher-level representation) and more context-aware acquisition devices which are aware of the existence of other cameras which can contribute to the creation of the full scene. This requires a step change in how we design and program these systems. Current FPGA technology such as the Xilinx Virtex-7 FPGA, offers a huge performance capability (over 6.7 Giga Multiply-Accumulate per second and up to 30 Terabits/s of memory bandwidth) and better power efficiency than GPUs. Currently FPGA solutions are created by aggregating powerful intellectual property (IP) cores together with soft cores, but the resulting performance is limited by the overall systems architecture and programmability is severely limited. Hence, there is a clear need to derive a FPGA system architecture that best matches the algorithmic requirements but that is programmable in software for a range of algorithms in the application domain. By considering the model of computation and programming model from the outset, we propose to create a highly powerful platform for a range of image processing algorithms. The proposal combines the FPGA processor design expertise in Queen's University (Woods), with the software language and compiler research (Michaelson) and image processing expertise (Wallace) at Heriot-Watt University. A key aspect is to ensure close interaction between the processor development and software languages and representation, in order to ensure the creation of a processor architecture configuration that is programmable in software. The research looks to radically alter the design of front end image processing systems by offering the performance of FPGA solutions with the programmability of processor solution